Battery local reaction anomaly detection method based on magnetic field change direction difference

Abstract

The invention discloses a battery local reaction anomaly detection method based on magnetic field change direction difference, and belongs to the technical field of battery detection. According to the method, magnetic field space distribution images of a standard reference battery and a target to-be-detected battery are obtained, local magnetic field change gradient direction vector fields in the X direction and the Y direction are extracted, and an included angle consistency map between the direction vector fields is constructed, so that the recombination or disturbance phenomenon of a reaction path of the target to-be-detected battery in a local space region is identified. The method does not need to depend on a global mean value or a template library, carries out point-by-point judgment based on spatial direction structural similarity, and has the advantages of high physical interpretability, clear anomaly positioning, high adaptability and the like. Local abnormal feature distribution is visually analyzed by means of directional structure difference distribution, and a disturbance type and a potential mechanism can be deduced in combination with a spatial form. The method is suitable for a plurality of application scenes such as battery consistency evaluation, process defect identification, electrode aging tracking and cell structure design optimization.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery detection, and in particular relates to a method for detecting abnormal local reactions of batteries based on differences in magnetic field change directions. Background Art

[0002] Currently, lithium-ion batteries are widely used in consumer electronics, new energy vehicles, and energy storage systems, and their performance, safety, and consistency have attracted much attention. Batteries inevitably exhibit non-uniform reaction behaviors during charge and discharge operations. This is especially true under conditions of inconsistent materials, complex structural designs, or local stress and thermal disturbances. Spatial heterogeneity phenomena such as localized reaction enhancement, polarization accumulation, and hot spot formation are prone to occur. These non-uniform behaviors may cause fluctuations in battery performance in the short term and may induce local failures or even thermal runaway in the long term. The ability to identify and regulate such non-uniform reactions has become a core issue in the screening and design optimization of high-quality batteries.

[0003] Currently, the assessment of battery status mainly relies on monitoring methods of single-point or global parameters such as overall voltage, current, and temperature, which makes it difficult to capture the dynamic evolution characteristics of local reactions within the battery. Indicators such as voltage platforms, internal resistance changes, and electrochemical impedance spectroscopy (EIS) can indirectly reflect certain performance trends, but lack the ability to analyze the spatial distribution of non-uniformity, making them difficult to use for early anomaly identification or operational adjustment capability assessment. In addition, some spatial resolution methods such as X-ray, thermal imaging, or neutron imaging have limitations such as high cost, low throughput, or the inability to be embedded in mass production processes. Therefore, there is an urgent need for a new method for detecting local abnormal reactions that combines spatial resolution capabilities, dynamic response sensitivity, and engineering feasibility to provide support for battery cell optimization design, in-situ detection, and fault tracing. Summary of the Invention

[0004] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a battery local reaction anomaly detection method based on the difference in magnetic field change direction. It can be based on non-invasive magnetic field detection, by constructing a directional vector field of the magnetic field change quantity, and performing comparative analysis between the standard reference battery and the target battery to be tested, to achieve spatial positioning and visual judgment of reaction path anomalies caused by internal current density redistribution. It overcomes the problems of traditional methods relying on global amplitude, lacking spatial direction resolution capability, and insensitivity to weak local disturbances. It can significantly improve the ability to resolve structural anomalies inside the battery, and has stronger physical interpretability and applicability.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for detecting abnormal local battery reactions based on differences in magnetic field change directions includes the following steps:

[0007] Step 1: Under constant current conditions, obtain the magnetic field distribution data of the standard reference battery and the target battery at different times during operation. , and , based on the initial reference state , calculate the change of magnetic field distribution at each moment , and further calculate the vector modulus of the magnetic field distribution change , which is used to map the spatial dynamic changes of the non-uniform reactions in the battery electrode plane, where , , 1 represents the standard reference battery, 2 represents the target battery to be tested, the xy direction is the length and width plane direction of the battery, and the z direction is the battery thickness direction perpendicular to the length and width plane;

[0008] Step 2: Magnetic field distribution change vector modulus of the standard reference battery and the target battery to be tested exist and Directional derivatives are calculated in each direction to construct the direction vector field of the standard reference battery and the target battery to be tested. and , the direction vector field is used to represent the local trend of the direction of magnetic field change;

[0009] Step 3: For each spatial position point , calculate the cosine difference of the angle between the direction vectors of the standard reference battery and the target battery to be tested, and construct the distribution of the direction structure difference:

[0010] , whose value range is 0-2;

[0011] Step 4: Distribution based on directional structural differences The position and shape of the medium and high value areas are used to determine whether the target battery under test has local reaction abnormalities and their spatial distribution characteristics: (1) If at a certain moment This means that the current changes of the two batteries at this point are in exactly the same direction and there is no abnormality; (2) If at a certain moment This means that the difference in the direction of the current change of the two batteries at this point is less than 90°, that is, there is a slight reaction abnormality; (3) If at a certain moment This means that the difference in the direction of the current change of the two batteries at this point is greater than or equal to 90°, and there is a strong reaction abnormality; (4) If at a certain moment When , it means that the current change direction of the two batteries at this location is 180° reversed, and severe local degradation or failure is very likely to occur;

[0012] Step 5: Draw the distribution of directional structure differences based on different test time points , analyze the evolution trend of the current change path of the target battery under test relative to the standard reference battery during operation.

[0013] Furthermore, in step 2, the method for calculating the modulus of the magnetic field distribution change vector is:

[0014] .

[0015] Furthermore, in step 2, the derivative calculation is implemented by a two-dimensional Sobel convolution operator, which has the advantages of directional enhancement and noise suppression. Specifically, the following convolution kernel is used:

[0016] ,

[0017] The directional derivatives obtained after the convolution operation are:

[0018] ,

[0019] Furthermore, the standard reference battery and the target battery to be tested construct a direction vector field and It is constructed by the following normalization formula:

[0020] .

[0021] Preferably, the battery comprises a laminated battery or a wound battery.

[0022] Preferably, the magnetic field measuring device for the magnetic field distribution data includes an array magnetic sensor device or a scanning magnetic sensor device.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. This method uses the changes in magnetic field distribution at different time points during battery operation as a basis to calculate its gradient directional structure within the spatial plane, reflecting the directional change trend caused by internal current density redistribution. This method is highly sensitive to changes in reaction paths caused by factors such as local electrode stress and decay. Compared to traditional methods that rely on magnetic field intensity values ​​or statistical analysis, this method does not rely on absolute amplitude values, making it more suitable for lateral consistency assessment and local anomaly screening between different types and structures of battery cells, and has good versatility and adaptability.

[0025] 2. By constructing a directional structural difference distribution based on the cosine difference of the angle, this method can visually display the reaction path changes between the target test battery and the standard reference battery in a spatial distribution, achieving accurate identification and visual location of abnormal areas. This method not only effectively distinguishes between normal and abnormal batteries, but also further distinguishes the types of abnormalities, such as path perturbations triggered by local factors, reaction imbalances caused by decay, and localized reaction anomalies caused by structure. This provides spatial data support and image evidence for fault tracing, structural optimization, and automated screening, and is suitable for battery cell condition assessment and quality grading under various operating conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flowchart of the overall process of the detection method of the present invention;

[0027] Figure 2 is the vector modulus of the magnetic field distribution change Schematic diagram;

[0028] Figure 3 Schematic diagram of the direction vector field of the standard reference battery and the target battery to be tested;

[0029] Figure 4 Schematic diagram of the distribution of directional structural differences between the standard reference battery and the target battery under test;

[0030] Figure 5 Schematic diagram of the structural differences between the standard reference battery and the locally squeezed battery at different test times;

[0031] Figure 6 Schematic diagram of the directional structural differences between standard reference batteries and degraded batteries at different test times. DETAILED DESCRIPTION

[0032] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only part of the embodiments of the invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] Example 1

[0034] This embodiment provides a method for detecting abnormal local reactions of batteries based on the difference in the direction of magnetic field changes. Figure 1 As shown, the method includes the following specific steps:

[0035] Step 1: Under constant current conditions, obtain the magnetic field distribution data of the standard reference battery and the target battery at different times during operation. , and , based on the initial reference state , calculate the change vector of magnetic field distribution at each moment , and further calculate the vector modulus of the magnetic field distribution change , which is used to map the spatial dynamic changes of the non-uniform reactions in the battery electrode plane, where , , 1 represents the standard reference battery, 2 represents the target battery to be tested, the xy direction is the length and width plane direction of the battery, and the z direction is the battery thickness direction perpendicular to the length and width plane;

[0036] In this embodiment, four 5Ah wound soft-pack batteries are used as examples for testing. Battery 1 is used as a standard reference battery, Battery 2 is a normal battery of the same type to be tested, Battery 3 is a locally squeezed battery of the same type to be tested, and Battery 4 is a decayed battery of the same type to be tested. According to the test method in step 1, the test plane is a plane 5mm higher than the battery surface, the test area is 65mm*70mm, the test interval is 5mm, and the magnetic field distribution data at different times during the battery operation are obtained under 1C constant current conditions. , and Measurements are taken based on the initial reference state , calculate the change of magnetic field distribution at each moment , and further calculate the vector modulus of the magnetic field distribution change , which is used to map the spatial dynamic changes of the non-uniform reactions in the battery electrode plane, where , Refers to battery 1, battery 2, battery 3 and battery 4, and the vector modulus of the magnetic field distribution change like Figure 2 As shown;

[0037] Step 2: Magnetic field distribution change vector modulus of the standard reference battery and the target battery to be tested exist and Directional derivatives are calculated in each direction to construct the direction vector field of the standard reference battery and the target battery to be tested. and , the direction vector field is used to represent the local trend of the direction of magnetic field change;

[0038] In this embodiment, the magnetic field distribution change vector modulus of the standard reference battery 1 and the target test battery 2, battery 3 and battery 4 is exist and Directional derivatives are calculated in each direction to construct the direction vector field of the standard reference battery and the target battery to be tested. 、 、 and ,like Figure 3 As shown, the direction vector field is used to represent the local trend of the direction of magnetic field change.

[0039] Step 3: For each spatial position point , calculate the cosine difference of the angle between the direction vectors of the standard reference battery and the target battery to be tested, and construct the distribution of the direction structure difference:

[0040] , whose value range is 0-2;

[0041] In this embodiment, the calculation standard reference battery 1 and the target test battery 2, battery 3, battery 4 at each spatial position are respectively The cosine difference of the angle between the direction vectors is used to construct the direction structure difference distribution. The results are as follows Figure 4 As shown, Figure 4 (a) is a schematic diagram of the local extrusion site of battery 3, Figure 4 (b)-(d) are schematic diagrams showing the distribution of directional structural differences between battery 1, battery 2, battery 3, and battery 4, respectively;

[0042] Step 4: Distribution based on directional structural differences The position and shape of the medium and high value areas are used to determine whether there is a local reaction abnormality in the target battery to be tested, and its spatial distribution characteristics: (1) If at a certain moment This means that the current changes of the two batteries at this point are in exactly the same direction and there is no abnormality; (2) If at a certain moment This means that the difference in the direction of the current change of the two batteries at this point is less than 90°, that is, there is a slight reaction abnormality; (3) If at a certain moment This means that the difference in the direction of the current change of the two batteries at this point is greater than or equal to 90°, and there is a strong reaction abnormality; (4) If at a certain moment When , it means that the current change direction of the two batteries at this location is 180° reversed, and severe local degradation or failure is very likely to occur;

[0043] In this embodiment, Figure 4 (b) It can be seen that the standard reference battery 1 and the normal battery 2 1e -7 The order of magnitude indicates that battery 1 and battery 2 have high consistency and no difference in internal reaction changes; Figure 4 (c) It can be seen that the current change direction of battery 3 is obviously reversed at the local compression site, with an angle greater than 90°. This shows that due to the compression in this area, the current change does not propagate into the battery like in battery 1, but propagates toward the tab. Figure 4(d) It can be seen that after the degradation of battery 4, the current change direction of the bottom part of the battery reverses and points to the center area of ​​the battery, indicating that there may be uneven degradation inside the battery, resulting in a change in the internal reaction equilibrium path;

[0044] Step 5: Draw the distribution of directional structure differences based on different test time points , analyze the current change path evolution trend of the target battery under test relative to the standard reference battery during operation;

[0045] In this embodiment, the directional structure difference distribution of the standard reference battery and the local extrusion battery 3 at different test time points is Draw, such as Figure 5 As shown in Figure 3, as the reaction of battery 3 progresses during operation, its main affected area is concentrated at the site where the extrusion is performed, but more highlighted areas appear inside it, indicating that the impact of the extrusion on the battery will accumulate over time and affect more areas; Figure 6 As shown in the figure, the reaction redistribution path of battery 4 shows a large-scale directional change relative to the standard reference battery at the beginning of discharge, and there is no uniform change pattern, indicating that the decay leads to more significant unevenness in the reaction activity within the battery plane. As the discharge progresses, the direction of the battery body tends to be consistent. This is because the reaction redistribution mainly diffuses from the tabs to the interior of the battery. The overall change trend will not change due to the influence of the structure during the entire discharge process, but this difference is further transferred to the bottom area of ​​the battery.

[0046] The detection method of the present invention does not rely on a global mean or template library, but instead makes point-by-point judgments based on spatial structural similarity. It offers strong physical interpretability, clear anomaly localization, and high adaptability. It is suitable for consistency comparison and anomaly screening between cells of different structures and states, and boasts the advantages of non-destructiveness and spatial and temporal resolution. It has excellent engineering adaptability and promotional value in practical application scenarios such as battery production consistency assessment, localized degradation / fault identification, and structural design optimization.

[0047] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A method for detecting abnormal local battery reactions based on the difference in magnetic field change directions, characterized in that: The following steps are involved: Step 1: Under constant current conditions, obtain the magnetic field distribution data of the standard reference battery and the target battery at different times during operation. , and , based on the initial reference state , calculate the change of magnetic field distribution at each moment , and further calculate the vector modulus of the magnetic field distribution change , which is used to map the spatial dynamic changes of the non-uniform reactions in the battery electrode plane, where , , 1 represents the standard reference battery, 2 represents the target battery to be tested, the xy direction is the length and width plane direction of the battery, and the z direction is the battery thickness direction perpendicular to the length and width plane; Step 2: Magnetic field distribution change vector modulus of the standard reference battery and the target battery to be tested exist and Directional derivatives are calculated in each direction to construct the direction vector field of the standard reference battery and the target battery to be tested. and , the direction vector field is used to represent the local trend of the direction of magnetic field change; Step 3: For each spatial position point , calculate the cosine difference of the angle between the direction vectors of the standard reference battery and the target battery to be tested, and construct the distribution of the direction structure difference: , whose value range is 0-2; Step 4: Distribution based on directional structural differences The position and shape of the medium and high value areas are used to determine whether the target battery under test has local reaction abnormalities and their spatial distribution characteristics: (1) If at a certain moment This means that the current changes of the two batteries at this point are in exactly the same direction and there is no abnormality; (2) If at a certain moment This means that the difference in the direction of the current change of the two batteries at this point is less than 90°, that is, there is a slight reaction abnormality; (3) If at a certain moment This means that the difference in the direction of the current change of the two batteries at this point is greater than or equal to 90°, and there is a strong reaction abnormality; (4) If at a certain moment When , it means that the current change direction of the two batteries at this location is 180° reversed, and severe local degradation or failure is very likely to occur; Step 5: Draw the distribution of directional structure differences based on different test time points , analyze the evolution trend of the current change path of the target battery under test relative to the standard reference battery during operation.

2. The method according to claim 1, wherein: In step 2, the method for calculating the modulus of the magnetic field distribution change vector is: 。 3. The method according to claim 1, wherein: In step 2, the derivative calculation is implemented by a two-dimensional Sobel convolution operator, which has the advantages of directional enhancement and noise suppression. Specifically, the following convolution kernel is used: ， The directional derivatives obtained after the convolution operation are: ， 。 4. The method according to claim 1, wherein: The standard reference battery and the target battery to be tested construct a direction vector field and It is constructed by the following normalization formula: 。 5. The method according to claim 1, wherein: The battery includes a laminated battery or a wound battery.

6. The method according to claim 1, wherein: The magnetic field measuring device for the magnetic field distribution data includes an array magnetic sensor device or a scanning magnetic sensor device.

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